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Record W2070182380 · doi:10.1300/j010v43n04_02

Social Support and Health Outcomes in a Multicultural Urban Population

2006· article· en· W2070182380 on OpenAlexaffabout
Robin Wright

Bibliographic record

VenueSocial Work in Health Care · 2006
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsMcGill University
Fundersnot available
KeywordsSocial supportMental healthMetropolitan areaImmigrationHealth equityPsychologyAcculturationMulticulturalismEthnic groupPopulationRace and healthSocial determinants of healthGerontologyPublic healthMedicineEnvironmental healthSocial psychologySociologyPsychiatryGeographyNursing

Abstract

fetched live from OpenAlex

Data from the Ontario Health Survey were used to examine the relationship between levels of social support and general health, suicidal ideation, family functioning, and utilization of health services among Metropolitan Toronto cultural populations 16-59 years of age (N = 2684). The results of this study provided some support for the hypothesis that social support variables correlate with general health status. Results also show that being a visible minority immigrant is not a risk factor for any of the health outcomes considered here. This finding is not in accordance with the notion of social hardship, which visible minority immigrants purportedly experience in a predominantly white society. Overall, indicators of social support show stronger association with mental health outcomes than with physical health ones.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.893

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.397
Teacher spread0.364 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2006
Admission routes2
Has abstractyes

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